Statistical Physics of Spin Glasses and Information Processing
An Introduction
Series: International Series of Monographs on Physics; 111;
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Product details:
- Publisher OUP Oxford
- Date of Publication 19 July 2001
- ISBN 9780198509417
- Binding Paperback
- No. of pages256 pages
- Size 236x157x15 mm
- Weight 378 g
- Language English
- Illustrations numerous line figures, 2 halftones 0
Categories
Short description:
This superb book provides the reader with a general perspective of an interdisciplinary field between statistical physics and information sciences/engineering. It is effectively the only book on the subject, aside from a collection of papers published fourteen years ago. The field is a rapidly expanding one and this self-contained presentation will be sure to acquire a wide audience in physics and engineering.
MoreLong description:
Spin glasses are magnetic materials. Statistical mechanics, a subfield of physics, has been a powerful tool to theoretically analyse various unique properties of spin glasses. A number of new analytical techniques have been developed to establish a theory of spin glasses. Surprisingly, these techniques have turned out to offer new tools and viewpoints for the understanding of information processing problems, including neural networks, error-correcting codes, image restoration, and optimization problems. This book is one of the first publications of the past ten years that provide a broad overview of this interdisciplinary field. Most of the book is written in a self-contained manner, assuming only a general knowledge of statistical mechanics and basic probability theory. It provides the reader with a sound introduction to the field and to the analytical techniques necessary to follow its most recent developments.
... very enjoyable to read and often opening the reader's eye to new possibilities. This is a perfect introduction to the field for students and researchers who want to study problems in information science, including the use of physics in information processing
Table of Contents:
Mean-field theory of phase transitions
Mean-field theory of spin glasses
Replica symmetry breaking
Gauge theory of spin glasses
Error-correcting codes
Image restoration
Associative memory
Learning in perceptron
Optimization problems
A. Eigenvalues of the Hessian
B. Parisi equation
C. Channel coding theorem
D. Distribution and free energy of K-Sat
References
Index
